Ship drift

from datetime import datetime
from opendrift.models.shipdrift import ShipDrift

o = ShipDrift(loglevel=20)

o.add_readers_from_list([
    'https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml',
    'https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc',
    'https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml'
    ])

15:20:29 INFO    opendrift:509: OpenDriftSimulation initialised (version 1.13.1 / v1.13.1-12-gca7f755)

Seed ship elements at defined position and time Note: beam/length ratio is larger than allowed, but is then clipped internally

o.seed_elements(lon=5.0, lat=63.0, radius=1000, number=1000,
                time=datetime.utcnow(),
                length=80.0, beam=20.0, height=9.0, draft=4.0)

15:20:29 WARNING opendrift.models.shipdrift:181: Ratio of beam to length should be in range 0.12 to 0.18, given range is 0.25-0.25. Using border value.
15:20:29 INFO    opendrift.models.basemodel.environment:206: Adding a global landmask from GSHHG
15:20:33 INFO    opendrift.models.basemodel.environment:229: Fallback values will be used for the following variables which have no readers:
15:20:33 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_stokes_drift_x_velocity: 0.000000
15:20:33 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_stokes_drift_y_velocity: 0.000000
15:20:33 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_significant_height: 0.000000
15:20:33 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment: 0.000000

Running model

o.run(steps=24, stop_on_error=True)

15:20:33 INFO    opendrift:919: Using existing reader for land_binary_mask
15:20:33 INFO    opendrift:930: All points are in ocean
15:20:33 INFO    opendrift:2056: 2025-04-03 15:20:29.157117 - step 1 of 24 - 1000 active elements (0 deactivated)
15:20:33 INFO    opendrift.readers:61: Opening file with xr.open_dataset
15:20:34 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'x': 'x', 'y': 'y', 'time': 'time'}
15:20:34 INFO    opendrift.readers:61: Opening file with xr.open_dataset
15:20:35 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'time': 'time', 'x': 'x', 'y': 'y'}
15:20:35 INFO    opendrift.readers:61: Opening file with xr.open_dataset
15:20:38 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'y': 'rlat', 'x': 'rlon', 'time': 'time'}
15:20:40 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:40 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:41 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:41 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:43 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:43 INFO    opendrift:2056: 2025-04-03 16:20:29.157117 - step 2 of 24 - 1000 active elements (0 deactivated)
15:20:45 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:45 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:46 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:46 INFO    opendrift:2056: 2025-04-03 17:20:29.157117 - step 3 of 24 - 1000 active elements (0 deactivated)
15:20:48 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:48 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:48 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:48 INFO    opendrift:2056: 2025-04-03 18:20:29.157117 - step 4 of 24 - 1000 active elements (0 deactivated)
15:20:50 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:50 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:51 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:51 INFO    opendrift:2056: 2025-04-03 19:20:29.157117 - step 5 of 24 - 1000 active elements (0 deactivated)
15:20:53 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:53 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:54 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:54 INFO    opendrift:2056: 2025-04-03 20:20:29.157117 - step 6 of 24 - 1000 active elements (0 deactivated)
15:20:56 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:56 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:57 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:20:57 INFO    opendrift:2056: 2025-04-03 21:20:29.157117 - step 7 of 24 - 1000 active elements (0 deactivated)
15:20:59 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:20:59 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:00 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:21:00 INFO    opendrift:2056: 2025-04-03 22:20:29.157117 - step 8 of 24 - 1000 active elements (0 deactivated)
15:21:02 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:02 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:03 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:21:03 INFO    opendrift:2056: 2025-04-03 23:20:29.157117 - step 9 of 24 - 1000 active elements (0 deactivated)
15:21:05 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:05 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:05 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:21:05 INFO    opendrift:2056: 2025-04-04 00:20:29.157117 - step 10 of 24 - 1000 active elements (0 deactivated)
15:21:08 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:08 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:08 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:21:08 INFO    opendrift:2056: 2025-04-04 01:20:29.157117 - step 11 of 24 - 1000 active elements (0 deactivated)
15:21:10 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:10 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:11 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:21:11 INFO    opendrift:2056: 2025-04-04 02:20:29.157117 - step 12 of 24 - 1000 active elements (0 deactivated)
15:21:13 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:13 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:14 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:21:14 INFO    opendrift:2056: 2025-04-04 03:20:29.157117 - step 13 of 24 - 1000 active elements (0 deactivated)
15:21:16 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:16 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:16 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:21:16 INFO    opendrift:2056: 2025-04-04 04:20:29.157117 - step 14 of 24 - 1000 active elements (0 deactivated)
15:21:19 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:19 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:19 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:21:19 INFO    opendrift:2056: 2025-04-04 05:20:29.157117 - step 15 of 24 - 1000 active elements (0 deactivated)
15:21:21 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:21 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:22 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:21:22 INFO    opendrift:2056: 2025-04-04 06:20:29.157117 - step 16 of 24 - 1000 active elements (0 deactivated)
15:21:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:25 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:21:25 INFO    opendrift:2056: 2025-04-04 07:20:29.157117 - step 17 of 24 - 1000 active elements (0 deactivated)
15:21:27 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:27 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:28 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:21:28 INFO    opendrift:2056: 2025-04-04 08:20:29.157117 - step 18 of 24 - 1000 active elements (0 deactivated)
15:21:29 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:29 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:30 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:21:30 INFO    opendrift:2056: 2025-04-04 09:20:29.157117 - step 19 of 24 - 1000 active elements (0 deactivated)
15:21:32 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:32 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:33 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:21:33 INFO    opendrift:2056: 2025-04-04 10:20:29.157117 - step 20 of 24 - 1000 active elements (0 deactivated)
15:21:35 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:35 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:36 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:21:36 INFO    opendrift:2056: 2025-04-04 11:20:29.157117 - step 21 of 24 - 1000 active elements (0 deactivated)
15:21:38 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:38 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:39 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:21:39 INFO    opendrift:2056: 2025-04-04 12:20:29.157117 - step 22 of 24 - 1000 active elements (0 deactivated)
15:21:41 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:41 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:41 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:21:41 INFO    opendrift:2056: 2025-04-04 13:20:29.157117 - step 23 of 24 - 1000 active elements (0 deactivated)
15:21:43 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:43 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:44 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
15:21:44 INFO    opendrift:2056: 2025-04-04 14:20:29.157117 - step 24 of 24 - 1000 active elements (0 deactivated)
15:21:46 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:46 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
15:21:46 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction

<xarray.Dataset> Size: 2MB
Dimensions:                                                                              (
                                                                                          trajectory: 1000,
                                                                                          time: 25)
Coordinates:
  * trajectory                                                                           (trajectory) int64 8kB ...
  * time                                                                                 (time) datetime64[ns] 200B ...
Data variables: (12/24)
    status                                                                               (trajectory, time) float32 100kB ...
    moving                                                                               (trajectory, time) float32 100kB ...
    age_seconds                                                                          (trajectory, time) float32 100kB ...
    origin_marker                                                                        (trajectory, time) float32 100kB ...
    lon                                                                                  (trajectory, time) float32 100kB ...
    lat                                                                                  (trajectory, time) float32 100kB ...
    ...                                                                                   ...
    x_sea_water_velocity                                                                 (trajectory, time) float32 100kB ...
    y_sea_water_velocity                                                                 (trajectory, time) float32 100kB ...
    sea_surface_wave_stokes_drift_x_velocity                                             (trajectory, time) float32 100kB ...
    sea_surface_wave_stokes_drift_y_velocity                                             (trajectory, time) float32 100kB ...
    sea_surface_wave_significant_height                                                  (trajectory, time) float32 100kB ...
    sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment  (trajectory, time) float32 100kB ...
Attributes: (12/96)
    Conventions:                                                             ...
    standard_name_vocabulary:                                                ...
    featureType:                                                             ...
    title:                                                                   ...
    summary:                                                                 ...
    keywords:                                                                ...
    ...                                                                                                               ...
    geospatial_lon_units:                                                    ...
    geospatial_lon_resolution:                                               ...
    runtime:                                                                 ...
    geospatial_vertical_min:                                                 ...
    geospatial_vertical_max:                                                 ...
    geospatial_vertical_positive:                                            ...

xarray.Dataset

• Dimensions:
  • trajectory: 1000
  • time: 25
• Coordinates: (2)
  • trajectory
    (trajectory)
    int64
    0 1 2 3 4 5 ... 995 996 997 998 999

    cf_role :

    trajectory_id

    dtype :

    <class 'numpy.int32'>

    array([  0,   1,   2, ..., 997, 998, 999])

  • time
    (time)
    datetime64[ns]
    2025-04-03T15:20:29.157117 ... 2...

    standard_name :

    time

    long_name :

    time

    dtype :

    <class 'numpy.float64'>

    array(['2025-04-03T15:20:29.157117000', '2025-04-03T16:20:29.157117000',
           '2025-04-03T17:20:29.157117000', '2025-04-03T18:20:29.157117000',
           '2025-04-03T19:20:29.157117000', '2025-04-03T20:20:29.157117000',
           '2025-04-03T21:20:29.157117000', '2025-04-03T22:20:29.157117000',
           '2025-04-03T23:20:29.157117000', '2025-04-04T00:20:29.157117000',
           '2025-04-04T01:20:29.157117000', '2025-04-04T02:20:29.157117000',
           '2025-04-04T03:20:29.157117000', '2025-04-04T04:20:29.157117000',
           '2025-04-04T05:20:29.157117000', '2025-04-04T06:20:29.157117000',
           '2025-04-04T07:20:29.157117000', '2025-04-04T08:20:29.157117000',
           '2025-04-04T09:20:29.157117000', '2025-04-04T10:20:29.157117000',
           '2025-04-04T11:20:29.157117000', '2025-04-04T12:20:29.157117000',
           '2025-04-04T13:20:29.157117000', '2025-04-04T14:20:29.157117000',
           '2025-04-04T15:20:29.157117000'], dtype='datetime64[ns]')

• Data variables: (24)
  • status
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.int32'>

    valid_range :

    [0 0]

    flag_values :

    [0]

    flag_meanings :

    active

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)

  • moving
    (trajectory, time)
    float32
    1.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0

    dtype :

    <class 'numpy.int32'>

    minval :

    1

    maxval :

    1

    array([[1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           ...,
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.]], dtype=float32)

  • age_seconds
    (trajectory, time)
    float32
    0.0 3.6e+03 ... 8.28e+04 8.64e+04

    dtype :

    <class 'numpy.float32'>

    units :

    s

    minval :

    0.0

    maxval :

    86400.0

    array([[    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           ...,
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.]],
          dtype=float32)

  • origin_marker
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.int32'>

    unit :

    description :

    An integer kept constant during the simulation. Different values may be used for different seedings, to separate elements during analysis. With GUI, only a single seeding is possible.

    flag_values :

    [0]

    flag_meanings :

    Seed_0

    minval :

    0

    maxval :

    0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)

  • lon
    (trajectory, time)
    float32
    5.035 5.032 5.065 ... 5.084 5.088

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    axis :

    X

    minval :

    4.8855963

    maxval :

    5.457095

    array([[5.0348186, 5.032232 , 5.0652246, ..., 5.1843276, 5.1817927,
            5.170546 ],
           [5.007899 , 4.999175 , 5.0484548, ..., 5.13967  , 5.120901 ,
            5.065739 ],
           [5.0193124, 5.043465 , 5.0704074, ..., 5.239278 , 5.225534 ,
            5.2119184],
           ...,
           [5.0018587, 5.0194526, 5.055292 , ..., 5.2753177, 5.28084  ,
            5.2682176],
           [4.9773602, 4.977768 , 5.0019064, ..., 5.193281 , 5.216521 ,
            5.2485223],
           [4.9929357, 5.0104966, 5.033968 , ..., 5.108699 , 5.0836396,
            5.08825  ]], dtype=float32)

  • lat
    (trajectory, time)
    float32
    63.0 63.02 63.03 ... 62.9 62.89

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    axis :

    Y

    minval :

    62.77924

    maxval :

    63.123913

    array([[63.004982, 63.021458, 63.02728 , ..., 62.931896, 62.93572 ,
            62.921192],
           [63.008007, 63.015553, 63.012238, ..., 62.89931 , 62.896107,
            62.88045 ],
           [62.99621 , 62.99942 , 62.99094 , ..., 62.850883, 62.847412,
            62.83989 ],
           ...,
           [63.001423, 63.004852, 63.003803, ..., 62.931553, 62.904613,
            62.896946],
           [62.989754, 63.006844, 63.013374, ..., 63.027153, 63.01558 ,
            63.01729 ],
           [62.98824 , 62.984917, 62.98954 , ..., 62.899975, 62.899284,
            62.88908 ]], dtype=float32)

  • z
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    standard_name :

    z

    long_name :

    vertical position

    axis :

    Z

    positive :

    up

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)

  • orientation
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 1.0 1.0 1.0 1.0

    dtype :

    <class 'numpy.uint8'>

    units :

    1

    minval :

    0

    maxval :

    1

    array([[0., 0., 0., ..., 0., 0., 0.],
           [1., 1., 1., ..., 1., 1., 1.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [1., 1., 1., ..., 1., 1., 1.],
           [0., 0., 0., ..., 0., 0., 0.],
           [1., 1., 1., ..., 1., 1., 1.]], dtype=float32)

  • length
    (trajectory, time)
    float32
    80.0 80.0 80.0 ... 80.0 80.0 80.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    min :

    1

    max :

    500

    description :

    Length of ship

    level :

    1

    minval :

    80.0

    maxval :

    80.0

    array([[80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.],
           ...,
           [80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.]], dtype=float32)

  • height
    (trajectory, time)
    float32
    9.0 9.0 9.0 9.0 ... 9.0 9.0 9.0 9.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    min :

    1

    max :

    100

    description :

    Total height of ship (above and below waterline)

    level :

    1

    minval :

    9.0

    maxval :

    9.0

    array([[9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.],
           ...,
           [9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.]], dtype=float32)

  • draft
    (trajectory, time)
    float32
    4.0 4.0 4.0 4.0 ... 4.0 4.0 4.0 4.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    min :

    1

    max :

    30

    description :

    Draft of ship (depth below water)

    level :

    1

    minval :

    4.0

    maxval :

    4.0

    array([[4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.],
           ...,
           [4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.]], dtype=float32)

  • beam
    (trajectory, time)
    float32
    20.0 20.0 20.0 ... 20.0 20.0 20.0

    dtype :

    <class 'numpy.float32'>

    min :

    1

    max :

    70

    units :

    m

    description :

    Beam (width) of ship

    level :

    1

    minval :

    20.0

    maxval :

    20.0

    array([[20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.],
           ...,
           [20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.]], dtype=float32)

  • wind_drag_coeff
    (trajectory, time)
    float32
    0.815 0.815 0.815 ... 0.815 0.815

    dtype :

    <class 'numpy.float32'>

    units :

    1

    minval :

    0.815

    maxval :

    0.815

    array([[0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           ...,
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815]], dtype=float32)

  • water_drag_coeff
    (trajectory, time)
    float32
    1.32 1.32 1.32 ... 1.32 1.32 1.32

    dtype :

    <class 'numpy.float32'>

    units :

    1

    minval :

    1.32

    maxval :

    1.32

    array([[1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           ...,
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32]], dtype=float32)

  • jibeProbability
    (trajectory, time)
    float32
    0.04 0.04 0.04 ... 0.04 0.04 0.04

    dtype :

    <class 'numpy.float32'>

    units :

    1/h

    minval :

    0.04

    maxval :

    0.04

    array([[0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           ...,
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04]], dtype=float32)

  • x_wind
    (trajectory, time)
    float32
    4.935 3.844 ... -0.2964 -0.2964

    minval :

    -3.3067276

    maxval :

    5.5541673

    array([[ 4.935033  ,  3.844313  ,  2.5047333 , ...,  0.60136306,
             1.4434688 ,  1.4434688 ],
           [ 4.487396  ,  3.2861626 ,  2.155103  , ..., -0.51061904,
             0.9561048 ,  0.9561048 ],
           [ 5.472032  ,  4.2495213 ,  2.737911  , ..., -0.3238088 ,
             0.14534286,  0.14534286],
           ...,
           [ 5.1639934 ,  4.355396  ,  3.2606354 , ..., -0.08903482,
             0.45213923,  0.45213923],
           [ 3.9757502 ,  3.1576805 ,  2.0693395 , ...,  0.90685046,
             1.4045911 ,  1.4045911 ],
           [ 4.433837  ,  2.729554  ,  1.5876294 , ..., -0.71641564,
            -0.2963625 , -0.2963625 ]], dtype=float32)

  • y_wind
    (trajectory, time)
    float32
    -7.133 -7.63 ... -6.413 -6.413

    minval :

    -8.900605

    maxval :

    -5.205144

    array([[-7.1328206, -7.629641 , -8.020221 , ..., -6.4146934, -6.746211 ,
            -6.746211 ],
           [-6.836088 , -7.3499675, -7.7475963, ..., -6.92528  , -7.228582 ,
            -7.228582 ],
           [-7.507443 , -8.184621 , -8.243529 , ..., -6.569919 , -6.626877 ,
            -6.626877 ],
           ...,
           [-6.515346 , -7.067937 , -7.551975 , ..., -6.8028636, -7.087915 ,
            -7.087915 ],
           [-6.267667 , -7.099628 , -7.875086 , ..., -7.5827546, -7.421986 ,
            -7.421986 ],
           [-7.5325522, -7.9476557, -7.9265175, ..., -6.3524756, -6.413456 ,
            -6.413456 ]], dtype=float32)

  • land_binary_mask
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)

  • x_sea_water_velocity
    (trajectory, time)
    float32
    0.1154 0.1396 ... -0.02724 -0.02724

    minval :

    -0.18649474

    maxval :

    0.29504126

    array([[ 0.11541821,  0.13962388,  0.169568  , ..., -0.06412444,
            -0.07074055, -0.07074055],
           [ 0.11443361,  0.12851639,  0.15637477, ..., -0.05897418,
            -0.05467384, -0.05467384],
           [ 0.10821756,  0.12933122,  0.14953156, ..., -0.1482016 ,
            -0.1504926 , -0.1504926 ],
           ...,
           [ 0.10886751,  0.12799083,  0.15421176, ..., -0.09388407,
            -0.11686714, -0.11686714],
           [ 0.1012437 ,  0.11903372,  0.14356494, ...,  0.02306477,
            -0.00279053, -0.00279053],
           [ 0.10218025,  0.11886998,  0.14355497, ..., -0.04058334,
            -0.02723798, -0.02723798]], dtype=float32)

  • y_sea_water_velocity
    (trajectory, time)
    float32
    0.3458 0.3386 ... 0.2258 0.2258

    minval :

    -0.09090725

    maxval :

    0.35996652

    array([[0.34584555, 0.3385885 , 0.32333124, ..., 0.11191502, 0.14004353,
            0.14004353],
           [0.34012908, 0.32933444, 0.3237862 , ..., 0.13397376, 0.17413369,
            0.17413369],
           [0.34928524, 0.348275  , 0.32460243, ..., 0.04605756, 0.07744611,
            0.07744611],
           ...,
           [0.3448077 , 0.34362805, 0.32615194, ..., 0.06182518, 0.08708966,
            0.08708966],
           [0.34005857, 0.32412726, 0.30855462, ..., 0.18260884, 0.18303317,
            0.18303317],
           [0.34656435, 0.3483369 , 0.32546306, ..., 0.17128702, 0.22583634,
            0.22583634]], dtype=float32)

  • sea_surface_wave_stokes_drift_x_velocity
    (trajectory, time)
    float32
    0.09572 0.09159 ... 0.004351

    minval :

    -0.0057008835

    maxval :

    0.100321256

    array([[ 0.09571528,  0.09159348,  0.08456505, ...,  0.00391257,
             0.00549363,  0.00549363],
           [ 0.09567811,  0.09115266,  0.08395929, ...,  0.0013362 ,
             0.00296078,  0.00296078],
           [ 0.09430792,  0.08896989,  0.08232875, ..., -0.00032892,
            -0.00041083, -0.00041083],
           ...,
           [ 0.0946603 ,  0.08934795,  0.08326093, ...,  0.00433819,
             0.0032457 ,  0.0032457 ],
           [ 0.09339252,  0.09008247,  0.08454   , ...,  0.01223146,
             0.01212628,  0.01212628],
           [ 0.09322632,  0.0872525 ,  0.08210708, ...,  0.00181946,
             0.00435114,  0.00435114]], dtype=float32)

  • sea_surface_wave_stokes_drift_y_velocity
    (trajectory, time)
    float32
    -0.05891 -0.06736 ... -0.08379

    minval :

    -0.10766296

    maxval :

    -0.0543398

    array([[-0.05890841, -0.06736363, -0.07246653, ..., -0.08990315,
            -0.09016368, -0.09016368],
           [-0.05847502, -0.0662466 , -0.0720408 , ..., -0.08963934,
            -0.08864436, -0.08864436],
           [-0.05700544, -0.06477229, -0.07089344, ..., -0.09856258,
            -0.10053942, -0.10053942],
           ...,
           [-0.05730693, -0.06481717, -0.07158113, ..., -0.09876278,
            -0.09902005, -0.09902005],
           [-0.05599969, -0.06516765, -0.07203647, ..., -0.08554062,
            -0.08802069, -0.08802069],
           [-0.05589261, -0.06270965, -0.0698873 , ..., -0.0860281 ,
            -0.0837888 , -0.0837888 ]], dtype=float32)

  • sea_surface_wave_significant_height
    (trajectory, time)
    float32
    4.158 4.274 4.235 ... 3.005 3.005

    minval :

    2.850826

    maxval :

    4.284276

    array([[4.1583757, 4.2736273, 4.235275 , ..., 3.019189 , 2.9677835,
            2.9677835],
           [4.156145 , 4.2559915, 4.2317233, ..., 3.026332 , 2.9845722,
            2.9845722],
           [4.1402874, 4.2561507, 4.222744 , ..., 2.9433532, 2.8937798,
            2.8937798],
           ...,
           [4.1429834, 4.2538037, 4.228976 , ..., 2.9667754, 2.9081936,
            2.9081936],
           [4.1064   , 4.236292 , 4.215642 , ..., 3.07295  , 3.0127301,
            3.0127301],
           [4.11156  , 4.2257833, 4.214063 , ..., 3.0426745, 3.0048232,
            3.0048232]], dtype=float32)

  • sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment
    (trajectory, time)
    float32
    8.487 8.603 8.559 ... 7.231 7.231

    minval :

    6.969445

    maxval :

    8.864316

    array([[8.48719  , 8.60286  , 8.55894  , ..., 7.292967 , 7.159675 ,
            7.159675 ],
           [8.484127 , 8.581127 , 8.559043 , ..., 7.2970076, 7.1805143,
            7.1805143],
           [8.48105  , 8.612691 , 8.561655 , ..., 7.2147145, 7.0607595,
            7.0607595],
           ...,
           [8.4800205, 8.606634 , 8.561689 , ..., 7.2009273, 7.06626  ,
            7.06626  ],
           [8.461946 , 8.573498 , 8.530148 , ..., 7.31381  , 7.172923 ,
            7.172923 ],
           [8.468583 , 8.609144 , 8.565199 , ..., 7.333196 , 7.2310233,
            7.2310233]], dtype=float32)

• Indexes: (2)
  • trajectory
    PandasIndex

    PandasIndex(Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,
           ...
           990, 991, 992, 993, 994, 995, 996, 997, 998, 999],
          dtype='int64', name='trajectory', length=1000))

  • time
    PandasIndex

    PandasIndex(DatetimeIndex(['2025-04-03 15:20:29.157117', '2025-04-03 16:20:29.157117',
                   '2025-04-03 17:20:29.157117', '2025-04-03 18:20:29.157117',
                   '2025-04-03 19:20:29.157117', '2025-04-03 20:20:29.157117',
                   '2025-04-03 21:20:29.157117', '2025-04-03 22:20:29.157117',
                   '2025-04-03 23:20:29.157117', '2025-04-04 00:20:29.157117',
                   '2025-04-04 01:20:29.157117', '2025-04-04 02:20:29.157117',
                   '2025-04-04 03:20:29.157117', '2025-04-04 04:20:29.157117',
                   '2025-04-04 05:20:29.157117', '2025-04-04 06:20:29.157117',
                   '2025-04-04 07:20:29.157117', '2025-04-04 08:20:29.157117',
                   '2025-04-04 09:20:29.157117', '2025-04-04 10:20:29.157117',
                   '2025-04-04 11:20:29.157117', '2025-04-04 12:20:29.157117',
                   '2025-04-04 13:20:29.157117', '2025-04-04 14:20:29.157117',
                   '2025-04-04 15:20:29.157117'],
                  dtype='datetime64[ns]', name='time', freq='h'))

• Attributes: (96)

  Conventions :

  CF-1.11, ACDD-1.3

  standard_name_vocabulary :

  CF Standard Name Table v85

  featureType :

  trajectory

  title :

  OpenDrift trajectory simulation

  summary :

  Output from simulation with OpenDrift framework

  keywords :

  trajectory, drift, lagrangian, simulation

  history :

  Created 2025-04-03 15:20:33.132041

  date_created :

  2025-04-03T15:20:33.132050

  source :

  Output from simulation with OpenDrift

  model_url :

  https://github.com/OpenDrift/opendrift

  opendrift_class :

  ShipDrift

  opendrift_module :

  opendrift.models.shipdrift

  readers :

  odict_keys(['LazyReader: https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'LazyReader: https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc', 'LazyReader: https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml', 'global_landmask'])

  time_coverage_start :

  2025-04-03 15:20:29.157117

  time_step_calculation :

  1:00:00

  time_step_output :

  1:00:00

  config_environment:constant:x_wind :

  None

  config_environment:fallback:x_wind :

  None

  config_environment:constant:y_wind :

  None

  config_environment:fallback:y_wind :

  None

  config_environment:constant:land_binary_mask :

  None

  config_environment:fallback:land_binary_mask :

  None

  config_environment:constant:x_sea_water_velocity :

  None

  config_environment:fallback:x_sea_water_velocity :

  None

  config_environment:constant:y_sea_water_velocity :

  None

  config_environment:fallback:y_sea_water_velocity :

  None

  config_environment:constant:sea_surface_wave_stokes_drift_x_velocity :

  None

  config_environment:fallback:sea_surface_wave_stokes_drift_x_velocity :

  0

  config_environment:constant:sea_surface_wave_stokes_drift_y_velocity :

  None

  config_environment:fallback:sea_surface_wave_stokes_drift_y_velocity :

  0

  config_environment:constant:sea_surface_wave_significant_height :

  None

  config_environment:fallback:sea_surface_wave_significant_height :

  0

  config_environment:constant:sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  None

  config_environment:fallback:sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  0

  config_general:use_auto_landmask :

  True

  config_drift:current_uncertainty :

  0

  config_drift:current_uncertainty_uniform :

  0

  config_drift:max_speed :

  2.0

  config_readers:max_number_of_fails :

  1

  config_general:simulation_name :

  config_general:coastline_action :

  stranding

  config_general:coastline_approximation_precision :

  0.001

  config_general:time_step_minutes :

  60

  config_general:time_step_output_minutes :

  None

  config_seed:ocean_only :

  True

  config_seed:number :

  1

  config_drift:max_age_seconds :

  None

  config_drift:advection_scheme :

  euler

  config_drift:horizontal_diffusivity :

  100.0

  config_drift:profiles_depth :

  50

  config_drift:wind_uncertainty :

  0

  config_drift:relative_wind :

  False

  config_drift:deactivate_north_of :

  None

  config_drift:deactivate_south_of :

  None

  config_drift:deactivate_east_of :

  None

  config_drift:deactivate_west_of :

  None

  config_seed:origin_marker :

  0

  config_seed:z :

  0

  config_seed:orientation :

  random

  config_seed:length :

  80

  config_seed:height :

  8

  config_seed:draft :

  4.0

  config_seed:beam :

  10

  config_seed:wind_drag_coeff :

  1

  config_seed:water_drag_coeff :

  1

  config_seed:jibeProbability :

  0.04

  opendrift_version :

  1.13.1

  seed_geojson :

  {"features": [], "type": "FeatureCollection"}

  simulation_time :

  2025-04-03 15:20:33.194050

  reader_x_wind :

  ['https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc']

  reader_y_wind :

  ['https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc']

  reader_land_binary_mask :

  ['global_landmask']

  reader_x_sea_water_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_y_sea_water_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_stokes_drift_x_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_stokes_drift_y_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_significant_height :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  time_coverage_end :

  2025-04-04 15:20:29.157117

  time_coverage_duration :

  P1DT0H0M0S

  time_coverage_resolution :

  P0DT1H0M0S

  performance :

  -------------------- Reader performance: -------------------- global_landmask 0:00:00.0 total 0:00:00.0 preparing 0:00:00.0 reading 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml 0:00:16.2 total 0:00:00.0 preparing 0:00:16.0 reading 0:00:00.0 interpolation 0:00:00.0 interpolation_time 0:00:00.2 rotating vectors 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc 0:00:33.1 total 0:00:00.0 preparing 0:00:32.9 reading 0:00:00.2 interpolation 0:00:00.0 interpolation_time 0:00:00.2 rotating vectors 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml 0:00:17.7 total 0:00:00.0 preparing 0:00:17.5 reading 0:00:00.0 interpolation 0:00:00.0 interpolation_time 0:00:00.2 rotating vectors 0:00:00.0 masking -------------------- Performance: 1:17.9 total time 4.0 configuration 0.0 preparing main loop 0.0 moving elements to ocean 1:13.7 main loop 0.6 updating elements 0.0 cleaning up --------------------

  geospatial_bounds_crs :

  EPSG:4326

  geospatial_bounds_vertical_crs :

  EPSG:5831

  geospatial_lat_min :

  62.77924

  geospatial_lat_max :

  63.123913

  geospatial_lat_units :

  degrees_north

  geospatial_lat_resolution :

  point

  geospatial_lon_min :

  4.8855963

  geospatial_lon_max :

  5.457095

  geospatial_lon_units :

  degrees_east

  geospatial_lon_resolution :

  point

  runtime :

  0:01:17.903898

  geospatial_vertical_min :

  0.0

  geospatial_vertical_max :

  0.0

  geospatial_vertical_positive :

  up

Print and plot results

print(o)
o.plot(linecolor='orientation')
#o.animation(color='orientation', markersize=20, filename="orientation.gif", legend=['left','right'],colorbar=False,cmap='bwr')
o.animation(color='orientation', legend=['left','right'], markersize=20, colorbar=False, cmap='bwr')

===========================
--------------------
Reader performance:
--------------------
global_landmask
 0:00:00.0  total
 0:00:00.0  preparing
 0:00:00.0  reading
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml
 0:00:16.2  total
 0:00:00.0  preparing
 0:00:16.0  reading
 0:00:00.0  interpolation
 0:00:00.0  interpolation_time
 0:00:00.2  rotating vectors
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc
 0:00:33.1  total
 0:00:00.0  preparing
 0:00:32.9  reading
 0:00:00.2  interpolation
 0:00:00.0  interpolation_time
 0:00:00.2  rotating vectors
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml
 0:00:17.7  total
 0:00:00.0  preparing
 0:00:17.5  reading
 0:00:00.0  interpolation
 0:00:00.0  interpolation_time
 0:00:00.2  rotating vectors
 0:00:00.0  masking
--------------------
Performance:
 1:17.9 total time
    4.0 configuration
    0.0 preparing main loop
      0.0 moving elements to ocean
 1:13.7 main loop
      0.6 updating elements
    0.0 cleaning up
--------------------
===========================
Model:  ShipDrift     (OpenDrift version 1.13.1)
        1000 active ShipObject particles  (0 deactivated, 0 scheduled)
-------------------
Environment variables:
  -----
  land_binary_mask
     1) global_landmask
  -----
  x_sea_water_velocity
  y_sea_water_velocity
     1) https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml
     2) https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml
  -----
  x_wind
  y_wind
     1) https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc
  -----
  sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment
  sea_surface_wave_significant_height
  sea_surface_wave_stokes_drift_x_velocity
  sea_surface_wave_stokes_drift_y_velocity
     1) https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml

Discarded readers:

Time:
        Start: 2025-04-03 15:20:29.157117 UTC
        Present: 2025-04-04 15:20:29.157117 UTC
        Calculation steps: 24 * 1:00:00 - total time: 1 day, 0:00:00
        Output steps: 25 * 1:00:00
===========================

15:22:06 INFO    opendrift:4600: Saving animation to /root/project/docs/source/gallery/animations/example_shipdrift_0.gif...
15:22:22 INFO    opendrift:3036: Time to make animation: 0:00:17.499843